[ITK-users] [ITK] Medical Image Analysis IPython Notebooks

[Matt McCormick]

I was unaware of this wiki page (thanks!).  I added a link to that
page and a link to the course here:

  http://www.itk.org/Wiki/ITK/Documentation#Courses

This page is linked from the main ITK web page and from the
http://www.itk.org/ITK/help/documentation.html page.

Thanks again for sharing this wonderful resource! Well done!

Matt

On Mon, Dec 22, 2014 at 3:32 PM, Jim Miller <millerjv at gmail.com> wrote:
> How about we add a link to these off the ITK Wiki.  Perhaps off the page
>
> http://itk.org/Wiki/ITK/Course_Ware
>
>
> Jim
>
> On Dec 22, 2014, at 1:04 PM, Keraudren, Kevin
> <kevin.keraudren10 at imperial.ac.uk> wrote:
>
> Hi Brad,
>
> I am glad the notebooks are appreciated, all the credit goes to Ozan (in
> copy) who is the main author!
>
> If I understand correctly you are mentioning in your email the
> ImageRegistrationMethod which will be in the next release of SimpleITK
> (0.9.0):
>
> http://www.itk.org/SimpleITKDoxygen/html/classitk_1_1simple_1_1ImageRegistrationMethod.html
>   https://github.com/SimpleITK/SimpleITK/tree/next
>
> This will definitely be something to look at for the next iteration of these
> tutorials.
>
> Kind regards,
>
> Kevin
>
> ________________________________
> From: Bradley Lowekamp [blowekamp at mail.nih.gov]
> Sent: Monday, December 22, 2014 2:26 PM
> To: Keraudren, Kevin
> Cc: insight-users at itk.org Users; Oktay, Ozan
> Subject: Re: [ITK-users] Medical Image Analysis IPython Notebooks
>
> Hello Kevin,
>
> These notebooks look outstanding. Thank you very much for sharing.
>
> I very much like what you did here:
> http://nbviewer.ipython.org/github/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials/blob/master/tutorial_2/basics_reg.ipynb
> to illustrate the different metrics' values, and the impact of apply
> Gaussian smoothing to the images.
>
> Also please note that you were using the an experimental version of the
> ImageRegistrationMethod in SimpleITK which was based on ITKv3 registration
> frameworks. Since then the development has evolved to be based on the ITKv4
> registration framework and many, many features have been added.
>
> This includes a couple transform initializers which estimate some basic
> transform parameters and very importantly set the fixed parameter for the
> center of the transform. Additionally the interface to the transforms is
> much improved.
>
> Brad
>
> On Dec 20, 2014, at 5:24 AM, Kevin Keraudren
> <kevin.keraudren10 at imperial.ac.uk> wrote:
>
> Hi,
>
> The IPython notebooks used for the tutorials in the Medical Image Analysis
> course at Imperial College London are now on github:
> https://github.com/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials
>
> These might be of interest to the mailing list as they rely on SimpleITK and
> could be useful either as teaching material or example applications.
>
> They can be browsed directly in nbviewer:
> http://nbviewer.ipython.org/github/ozan-oktay/Medical-Image-Analysis-IPython-Tutorials/tree/master/
>
> The following blog post is a quick presentation of the github repository:
> http://kevin-keraudren.blogspot.co.uk/2014/12/medical-image-analysis-ipython-tutorials.html
>
> Please do not hesitate to let us  know if you have questions or comments
> regarding these tutorials.
>
> Kind regards,
>
> Kevin Keraudren,
> PhD student, Imperial College London
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> http://www.kitware.com/products/protraining.php
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